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NewsCatcher MCP Server for LlamaIndex 4 tools — connect in under 2 minutes

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NewsCatcher as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to NewsCatcher. "
            "You have 4 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in NewsCatcher?"
    )
    print(response)

asyncio.run(main())
NewsCatcher
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About NewsCatcher MCP Server

Connect NewsCatcher to any AI agent and access a massive, real-time news feed aggregator with powerful clustering and filtering capabilities.

LlamaIndex agents combine NewsCatcher tool responses with indexed documents for comprehensive, grounded answers. Connect 4 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

  • Real-Time Search — Search millions of articles instantly with keyword, language, country, and source filters
  • Latest News Feed — Get the most recent articles for any topic or publisher
  • News Clustering — Group similar stories to see how different outlets cover the same event
  • Source Discovery — List available news sources by country, topic, or language
  • Global Coverage — Access news from over 100,000 sources worldwide

The NewsCatcher MCP Server exposes 4 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect NewsCatcher to LlamaIndex via MCP

Follow these steps to integrate the NewsCatcher MCP Server with LlamaIndex.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 4 tools from NewsCatcher

Why Use LlamaIndex with the NewsCatcher MCP Server

LlamaIndex provides unique advantages when paired with NewsCatcher through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine NewsCatcher tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain NewsCatcher tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query NewsCatcher, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what NewsCatcher tools were called, what data was returned, and how it influenced the final answer

NewsCatcher + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the NewsCatcher MCP Server delivers measurable value.

01

Hybrid search: combine NewsCatcher real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query NewsCatcher to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying NewsCatcher for fresh data

04

Analytical workflows: chain NewsCatcher queries with LlamaIndex's data connectors to build multi-source analytical reports

NewsCatcher MCP Tools for LlamaIndex (4)

These 4 tools become available when you connect NewsCatcher to LlamaIndex via MCP:

01

get_latest_news

Use "q" for keywords, "topic" (e.g., "sports"), "countries" (e.g., "US"), or "sources" (e.g., "cnn.com"). Get the latest news articles for a topic or source

02

get_news_clusters

Get grouped news stories (clusters)

03

list_sources

Filter by "topic", "countries", or "lang". List available news sources

04

search_news

Use "q" for keywords, "lang" for language (e.g., "en"), "countries" for country codes (e.g., "US"), and "sort_by" (relevancy, date). Search for news articles using keywords and filters

Example Prompts for NewsCatcher in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with NewsCatcher immediately.

01

"Find latest news about 'Artificial Intelligence' in the US."

02

"Show me clusters for the topic 'Elections'."

03

"List all English news sources available for Sports."

Troubleshooting NewsCatcher MCP Server with LlamaIndex

Common issues when connecting NewsCatcher to LlamaIndex through the Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

NewsCatcher + LlamaIndex FAQ

Common questions about integrating NewsCatcher MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query NewsCatcher tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

Connect NewsCatcher to LlamaIndex

Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.